Pretprocesiranje i analiza velikih skupova podataka odabranim metodama pomoću programskog jezika R

undergraduate thesis

• Title (english): Big Data Pre-processing and Analysis Using Select Methods in Programming Language R
• Author: Ivan Jure Parać
• Mentor: Bogdan Okreša Đurić (mentor); MBZ: 367114
• Committee member: Markus Schatten (član povjerenstva); MBZ: 291806
• Granter: University of Zagreb; Faculty of Organization and Informatics; (Department of Theoretical and Applied Foundations of Information Sciences); Varaždin
• Defense date and country: 2021-08-30, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Information and Communication Sciences; Organization and Informatics

Abstract

The topic of this thesis is focused on preprocessing and analysis methods in the domain of big data. The theoretical part of the thesis is expected to include topics pertaining to the methods of preprocessing data (e.g. dealing with missing data, encoding data, sampling training vs. learning sets of data, feature scaling, etc.), and an overview of a set of select methods of big data analysis. The practical part of the thesis is expected to feature the application of some of the described methods on a chosen data set, implemented in programming language R.

• Keywords: umjetna inteligencija; strojno učenje; r; veliki podaci; big data; predprocesiranje
• Language: croatian
• URN:NBN: urn:nbn:hr:211:450170
• Study programme: Title: Information Systems; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to authenticated users
• Created on: 2021-09-06 04:01:31